Sorry in advance, these might be bad questions, as I don't have any interviews right now and thus no specific questions, but I'm trying to get a realistic picture of what technical questions come up when interviewing for Research Scientist or Research Engineer roles focused on diffusion, so I can prepare better in the future.
Here are some things I'm wondering about, but feel free to include other stuff not listed here, also don't have to answer all questions:
- How did you prepare? Any specific papers, books, courses etc?
- What kind of questions did they ask? Did you also need to prepare for system design and leetcode questions?
- What specific diffusion-related topics came up most often?
- For RS: Were there proof-heavy questions, derivations from scratch or discussions of open theoretical problems?
- For RE: How much emphasis was there on implementation details, scaling, evaluation, or real-world adaptations (to like different modalities I guess or real use cases)?
- Did they ask you to critique recent papers, propose extensions to existing diffusion work, or brainstorm new research directions on the spot?
- Any surprising or unusually hard technical questions you remember?
Thanks in advance!
Edit: I googled around, but couldn't find anything specific to interviews with diffusion. Seems to be an abundance of advice for general ML/DL theory and LLM theory, but nothing specific to diffusion.
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